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peakacom

peaka-mcp-server

Official
by peakacom

peaka_get_project_metadata

Read-only

Retrieve metadata for all catalogs, schemas, and tables in a Peaka project in a single call. Filter by catalog or schema to discover data structure before writing queries.

Instructions

Get metadata for all catalogs, schemas, and tables in the Peaka project in a single call. Optionally filter by catalogId and/or schemaName. Use this tool to discover the data structure before writing queries.

If you do not already know the projectId for the current task, call peaka_list_projects first and ask the user which project to use. Remember the chosen projectId for subsequent calls in this conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catalogIdNoOptional catalog ID to filter metadata by a specific catalog.
projectIdYesThe Peaka project ID to run against.
schemaNameNoOptional schema name to filter metadata by a specific schema.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.11.0

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context that the call returns all metadata in one request and supports optional filters, but it does not disclose output shape, pagination, or whether metadata is cached/refreshed. With read-only annotations, a 3 is appropriate: it adds some value but not deep behavioral detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded in the first sentence, and the following sentences provide prerequisite guidance without being excessively long. The instruction to remember the projectId is useful, though the separate workflow sentence could be tightened. Still, every sentence contributes meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a read-only metadata discovery operation with 3 well-documented parameters and no output schema. The description states what it returns at a high level, how to call it, and how to obtain the required projectId. It lacks a specific output shape, but for a broad discovery tool that's acceptable; it is otherwise complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds only a minor clarification that catalogId and/or schemaName can be used as filters, but it does not introduce meaning beyond what the property descriptions already state. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb+resource: "Get metadata for all catalogs, schemas, and tables in the Peaka project in a single call." This clearly separates it from the granular sibling tools like peaka_list_catalogs, peaka_list_schemas, and peaka_list_tables, since it emphasizes the single-call all-encompassing behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use this tool to discover the data structure before writing queries, which is clear usage context. It also gives an alternative workflow for obtaining the required projectId by calling peaka_list_projects first. It does not explicitly name exclusion cases or contrast with the sibling list_* tools, but it gives enough context to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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